Model Calibration and Parameter Estimation

Model Calibration and Parameter Estimation
Author: Ne-Zheng Sun
Publisher: Springer
Total Pages: 638
Release: 2015-07-01
Genre: Mathematics
ISBN: 1493923234

This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can be used as a reference for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for professionals such as petroleum engineers, mining engineers, chemists, mechanical engineers, biologists, biology and medical engineering, applied mathematicians, and others who perform mathematical modeling.

Parameter Estimation and Auto-calibration of the STREAM-C Model

Parameter Estimation and Auto-calibration of the STREAM-C Model
Author: Sumit Sinha
Publisher:
Total Pages:
Release: 2005
Genre: Rivers
ISBN:

The STREAM-C model is based on the same algorithm as implemented by the Steady Riverine Environmental Assessment Model (STREAM), a mathematical model for the dissolved oxygen (DO) distribution in freshwater streams used by Mississippi Department of Environmental Quality (MDEQ). Typically the water quality models are calibrated manually. In some cases where some objective criterion can be identified to quantify a successful calibration, an auto calibration may be preferable to the manual calibration approach. The auto calibration may be particularly applicable to relatively simple analytical models such as the steady-state STREAM-C model. Various techniques of parameter estimation were identified for the model. The model was then subjected to various techniques of parameter estimation identified and/or developed. The parameter estimates obtained by different techniques were tabulated and compared. A final recommendation regarding a preferable parameter estimation technique leading to auto calibration of the STREAM-C model was made.

Calibration of Watershed Models

Calibration of Watershed Models
Author: Qingyun Duan
Publisher: John Wiley & Sons
Total Pages: 356
Release: 2003-01-10
Genre: Science
ISBN: 087590355X

Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. These models are based on general mathematical descriptions of the watershed processes that transform natural forcing (e.g., rainfall over the landscape) into response (e.g., runoff in the rivers). The user of a watershed hydrology model must specify the model parameters before the model is able to properly simulate the watershed behavior.

Effective Groundwater Model Calibration

Effective Groundwater Model Calibration
Author: Mary C. Hill
Publisher: John Wiley & Sons
Total Pages: 475
Release: 2006-08-25
Genre: Technology & Engineering
ISBN: 0470041072

Methods and guidelines for developing and using mathematical models Turn to Effective Groundwater Model Calibration for a set of methods and guidelines that can help produce more accurate and transparent mathematical models. The models can represent groundwater flow and transport and other natural and engineered systems. Use this book and its extensive exercises to learn methods to fully exploit the data on hand, maximize the model's potential, and troubleshoot any problems that arise. Use the methods to perform: Sensitivity analysis to evaluate the information content of data Data assessment to identify (a) existing measurements that dominate model development and predictions and (b) potential measurements likely to improve the reliability of predictions Calibration to develop models that are consistent with the data in an optimal manner Uncertainty evaluation to quantify and communicate errors in simulated results that are often used to make important societal decisions Most of the methods are based on linear and nonlinear regression theory. Fourteen guidelines show the reader how to use the methods advantageously in practical situations. Exercises focus on a groundwater flow system and management problem, enabling readers to apply all the methods presented in the text. The exercises can be completed using the material provided in the book, or as hands-on computer exercises using instructions and files available on the text's accompanying Web site. Throughout the book, the authors stress the need for valid statistical concepts and easily understood presentation methods required to achieve well-tested, transparent models. Most of the examples and all of the exercises focus on simulating groundwater systems; other examples come from surface-water hydrology and geophysics. The methods and guidelines in the text are broadly applicable and can be used by students, researchers, and engineers to simulate many kinds systems.

Advances In Data-based Approaches For Hydrologic Modeling And Forecasting

Advances In Data-based Approaches For Hydrologic Modeling And Forecasting
Author: Bellie Sivakumar
Publisher: World Scientific
Total Pages: 542
Release: 2010-08-10
Genre: Science
ISBN: 9814464759

This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each — stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.

Modelling and Parameter Estimation of Dynamic Systems

Modelling and Parameter Estimation of Dynamic Systems
Author: J.R. Raol
Publisher: IET
Total Pages: 405
Release: 2004-08-13
Genre: Mathematics
ISBN: 0863413633

This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.

PARAMETER ESTIMATION AND AUTO-CALIBRATION FOR THE STREAM-C MODEL.

PARAMETER ESTIMATION AND AUTO-CALIBRATION FOR THE STREAM-C MODEL.
Author:
Publisher:
Total Pages:
Release: 2004
Genre:
ISBN:

The STREAMC model is based on the same algorithm as implemented by the Steady Riverine Environmental Assessment Model (STREAM), a mathematical model for the dissolved oxygen (DO) distribution in freshwater streams used by Mississippi Department of Environmental Quality (MDEQ). Typically the water quality models are calibrated manually. In some cases where some objective criterion can be identified to quantify a successful calibration, an auto calibration may be preferable to the manual calibration approach. The auto calibration may be particularly applicable to relatively simple analytical models such as the steady-state STREAMC model. Various techniques of parameter estimation were identified for the model. The model was then subjected to various techniques of parameter estimation identified and/or developed. The parameter estimates obtained by different techniques were tabulated and compared. A final recommendation regarding a preferable parameter estimation technique leading to the auto calibration of the STREAMC model was made.

Applied Uncertainty Analysis For Flood Risk Management

Applied Uncertainty Analysis For Flood Risk Management
Author: Keith J Beven
Publisher: World Scientific
Total Pages: 685
Release: 2014-01-13
Genre: Technology & Engineering
ISBN: 1783263121

This volume provides an introduction for flood risk management practitioners, up-to-date methods for analysis of uncertainty and its use in risk-based decision making. It addresses decision making for both short-term (real-time forecasting) and long-term (flood risk planning under change) situations. It aims primarily at technical practitioners involved in flood risk analysis and flood warning, including hydrologists, engineers, flood modelers, risk analysts and those involved in the design and operation of flood warning systems. Many experienced practitioners are now expected to modify their way of working to fit into the new philosophy of flood risk management. This volume helps them to undertake that task with appropriate attention to the surrounding uncertainties. The book will also interest and benefit researchers and graduate students hoping to improve their knowledge of modern uncertainty analysis.